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Record W2171538456 · doi:10.1139/p04-008

Correction de l'approximation de Kirchhoff par la méthode intégrale reformulée : cas des réflectivités de surfaces sinusoïdales

2004· article· en· W2171538456 on OpenAlexvenueno aff
Mint Bacar Matchiane, Faouzi Ghmari, Mohamed Salah Sifaoui

Bibliographic record

VenueCanadian Journal of Physics · 2004
Typearticle
Languageen
FieldMaterials Science
TopicOptical Coatings and Gratings
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsComputationTransverse planeIntegral equationPolarization (electrochemistry)Magnetic fieldDielectricMathematical analysisIterative methodRadiative transferOpticsQuantum mechanicsAlgorithmMathematics

Abstract

fetched live from OpenAlex

Using two different methods, we study the radiative properties of rough surfaces, such as the bidirectional or the hemispheric directional reflectivity. The first method, which we call exact, is the integral method (MI). It is based on the electromagnetic theory and Green's theorem to describe the system through a system of equations for the field and its normal derivative (sources) at the surface. The method is computation expensive, requiring the inversion of possibly large complex matrices. The second method (MIR), which we will use and for which we extend the validity to include transverse polarization, reformulates the integral method to solve it by an iterative approach. It has the advantage that its first iteration corresponds to the Kirchoff approximation (AK). The following (higher order) terms bring corrections to AK, while reducing notably the computation load. Our main purpose is to study the stability of the MIR and to find the limits of its validity when compared with the (exact) MI. Our numerical results were carried out for perfectly conducting or dielectric surfaces with sinusoidal roughness for two polarizations, transverse electric and transverse magnetic. [Journal translation]

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.263
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2004
Admission routes1
Has abstractyes

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